Large scale proteomics of circulating extracellular vesicles to reveal novel biomarkers for pancreatic cancer.

Abstract

523 Background: Robust biomarkers are urgently needed to assist in diagnosing pancreatic cancer. Earlier cancer diagnosis could increase survival rates by an estimated 5-fold and more reliable and real-time assessment of treatment effects in patients with cancer could improve quality of life and reduce healthcare costs. Isolation of circulating extracellular vesicles (cEVs) as ‘liquid biopsies’ offers an advantageous approach to diagnose and monitor disease status. Methods: We conducted a comprehensive proteomics study of cEVs from plasma samples to identify EV proteins that may be used as biomarkers for the diagnosis and prognosis of pancreatic cancer. Patients with pancreatic ductal adenocarcinoma (PDAC) of various tumor stages, chronic pancreatitis, intraductal papillary mucinous neoplasm (IPMN), and age-matched controls were enrolled. EVs were isolated directly from plasma samples using the affinity-based EVTrap method then subject to quantitation by liquid chromatography-tandem mass spectrometry. Results: A total of 124 patients (93 with PDAC, 12 with chronic pancreatitis, 8 with IPMN and 11 controls) were included in the discovery cohort. The isolation of EVs with EVtrap allowed the identification on average of 912 EV proteins per 100µL of sample. Principal component analysis of the cEV proteome showed clear separation between PDAC and benign pancreatic diseases. Individuals with IPMN were more closely related to controls, whereas chronic pancreatitis cases were more related to PDAC. At the functional level, we noted that cytokeratin, protein folding chaperons, and actin dynamics regulators were among protein clusters more highly altered in the cEV of patients with PDAC. We further identified new cEV markers associated with metastatic disease, such as PSMB4, RUVBL2, and ANKAR, as well as other EV proteins with strong correlation to prognosis, such as CRP, RALB, and CD55. Finally, we validated a 7-protein PDACEV signature in a validation cohort of 36 separate patients (24 with PDAC, 6 with chronic pancreatitis and 6 with IPMN) which yielded an 89% prediction accuracy for the diagnosis of PDAC. Conclusions: This study provides a valuable resource to the scientific community with a comprehensive catalog of novel proteins on circulating EVs that may assist in the development of novel biomarkers and improve the outcomes of patients with pancreatic cancer.